tptran

ofdm系统的简单仿真，基于matlab环境，可以借此更好的理解ofdm传输原理(simple simulation ofdm systems, based on the matlab environment, can take a better understanding of the principle of ofdm transmission)

说明：  指派问题 微粒群PSO算法 以时间为优化目标函数(Assignment of PSO PSO algorithm to optimize the objective function of time)

In a normal communication channel, it is often desirable to concentrate the information in as narrow a region of the frequency spectrum as possible in order to conserve available bandwidth and to reduce power. The basic spread spectrum technique, on the other hand, is designed to encode a stream of information by spreading the encoded data across as much of the frequency spectrum as possible. This allows the signal reception, even if there is interference on some frequencies. While there are many variations on spread spectrum communication, we concentrated on Direct Sequence Spread Spectrum encoding (DSSS). The DSSS method spreads the signal by multiplying it by a chip, a maximal length pseudorandom sequence modulated at a known rate. Since the host signals are in discrete-time format, we can use the sampling rate as the chip rate for coding.

PID解耦，用于多变量解耦，是个很好的例子，希望对大家有用(PID decoupling, for multi-variable decoupling is a good example, in the hope it would be useful)

本书用较少的数学知识阐明了小波分析的基本理论和应用。(wavelet)

33节点的配电网重构程序，基于粒子群算法。相当快速。但是需要再修改源码才可以重新生成数据。(33 node distribution network reconfiguration procedures, based on particle swarm optimization. Pretty fast. But the need to modify the source code before they can re-generate the data.)

u can calculate DCT clc inp = imread( Im1.jpg ) inp1 = imread( Im2.jpg ) A = double(inp(:,:,1)) B = double(inp1(:,:,1)) A1=double(blkproc(A,[8 8], dct2 )) B1=double(blkproc(B,[8 8], dct2 )) [r,c] = size(A1) r1 = [] for i=1:r for j=1:c if A1(i,j) > B1(i,j) r1(i,j)=A1(i,j) else r1(i,j)=B1(i,j) end end end r1= double(r1(:,:,1)) C=blkproc(r1,[8 8], idct2 ) round(C) C1=idct2(r1) figure imshow(uint8(C)) figure imshow(uint8(C1)) imwrite(uint8(C), dct8x8min.jpg )

economic load dispatch with emission

The PSNR is most commonly used as a measure of quality of reconstruction of lossy compression codecs (e.g., for image compression). The signal in this case is the original data, and the noise is the error introduced by compression

this archive shows some examples of how to design fir and iir filters